1. Field
The present invention relates to a three-dimensional (3D) image processing method, and more particularly, to data storing and processing methods (or apparatuses) which may efficiently perform a process of retrieving neighboring points between points stored in a leaf cell in a point-based 3D data expressing method.
2. Description of the Related Art
Currently, studies of a method for obtaining three-dimensional (3D) information through image matching after obtaining a depth image using a depth camera and then obtaining a color image using general Charge-Coupled Device (CCD)/Complementary Metal Oxide Semiconductor (CMOS) cameras have been attempted.
As examples of methods for representing the 3D information obtained as described above, a method using a triangular mesh, a method using point cloud, and the like may be given. The obtained 3D information may be transformed into an efficient representing structure after an appropriate modeling process is performed. In this manner, performance of the transformation or various processing and rendering after the transformation may significantly depend on efficiency of a data structure expressing 3D information.
In a mesh-based 3D information expressing method, neighboring pixels are connected using regularity of images and mesh connection information is generated to process images. According to the mesh based 3D information expressing method, noises, holes, and the like generated when obtaining the depth image may be relatively easily eliminated. However, the mesh based 3D information expressing method may require a stitching process with respect to overlapped portions of a plurality of pieces of image data, which is known as a significantly complex process, in order to generate a single 3D mesh model from the plurality of pieces of image data being different from a piece of image data.
Meanwhile, in a point-based 3D information expressing method, a relatively efficient 3D model may be generated in comparison with the mesh-based 3D information expressing method because 3D point data obtained from the plurality of pieces of the image is simply combined on a space. In this instance, the above described point data may be stored in a spatial data structure such as a kd-tree or an octree. The spatial data structure such as the octree used in a conventional point-based 3D information expressing method may not have connection information between points as in a polygon mesh method, and thereby retrieving of neighboring points required for performing various types of processing may require a great amount of time.